A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding

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Bayesianself-representationcausal learningconsciousness

2610.08792

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50%

1h ago

Abstract

The paper introduces the Bayesian Mirror Architecture (BMA), a framework for understanding consciousness through circular recursion and self-representations.

Reality Card

Core Claim

The BMA provides a foundational framework for emergent consciousness by defining a closed update mechanism that binds self-representations to abstract world models.

Method / Result

The paper defines a Causal Learning Regime (CLR) that diagnoses learnable causal structures in the environment.

Limitations

The framework may exhibit multiple coherent basins, complicating reproducibility and generalization of results.

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